An efficient ML approach to detect brain tumor using MRI images

An efficient ML approach to detect brain tumor using MRI images

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Bibliographische Detailangaben
Hauptverfasser:	Muktadir, MD. Arafat, Ullah, A.S.M Rahmat, Hossain, Emdad, Islam, MD. Jubayer, Munny, Tanjila Akter
Weitere Verfasser:	Alam, Md. Ashraful
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2024
Schlagworte:	Brain tumor Machine learning Deep neural network Magnetic resonance imaging Neural networks (Computer science) Deep learning (Machine learning) Magnetic resonance imaging.
Online Zugang:	http://hdl.handle.net/10361/22904

Ähnliche Einträge

In-depth analysis of deep learning architectures for brain tumor classification in MRI scans
von: Haque, Hossain MD. Hasibul, et al.
Veröffentlicht: (2024)

Enhancing multiclass brain tumor classification using deep learning: leveraging superior imaging representations to improve inferior modality performance
von: Hossain, Shah Md. Shakhawath, et al.
Veröffentlicht: (2024)

Intracranial hemorrhage detection using CNN-LSTM fusion model
von: Ahmed, Kazi sabab, et al.
Veröffentlicht: (2022)

Detection of multiple sclerosis using deep learning
von: Jannat, Sabila Al, et al.
Veröffentlicht: (2021)

Improvisation of Magnetic Resonance Imaging (MRI) with development and feasible evaluation of fiber optic sensors: a survey
von: Shabnam, Farzana, et al.
Veröffentlicht: (2018)

Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data
von: Mahbub, Riasat, et al.
Veröffentlicht: (2022)

Classification of different magnetic structures from image data using deep neural networks
von: Ibn Hasib, Fahad, et al.
Veröffentlicht: (2023)

The long road to Stockholm
von: Mansfield, P.

3D Brain image segmentation using 3D tiled convolution neural networks
von: Haque, Md Mahibul, et al.
Veröffentlicht: (2024)

An efficient deep learning approach to detect skin Cancer
von: Islam, Ashfaqul, et al.
Veröffentlicht: (2022)

Brain tumor detection through image processing
von: Azmim, Tahaziba, et al.
Veröffentlicht: (2021)

Prostate cancer detection using deep learning neural network with transfer learning approach
von: Badhon, Ariful Islam Mahmud, et al.
Veröffentlicht: (2022)

Visual object classification from fMRI data
von: Newaz, Syed Mishar, et al.
Veröffentlicht: (2022)

Corn leaf disease detection using deep convolution neural network
von: Rabbi, Rawhatur, et al.
Veröffentlicht: (2023)

A novel lightweight CNN approach for Bangladeshi sign language gesture recognition
von: Rahman, Aryan, et al.
Veröffentlicht: (2023)

Automatic brain tumor segmentation using U-ResUNet chain model approach
von: Alam, Mohd Tanjeem, et al.
Veröffentlicht: (2022)

An efficient deep learning approach for brain tumor detection using 3D convolutional neural network
von: Ali, Syed Muaz
Veröffentlicht: (2023)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
von: Sakir, Adnan, et al.
Veröffentlicht: (2023)

An Efficient deep learning approach to detect Brain Tumor using MRI images
von: Islam, Annur Tasnim, et al.
Veröffentlicht: (2022)

An efficient deep learning approach to detect skin cancer using image data
von: Chowdhury, Yaser Al Rahman, et al.
Veröffentlicht: (2023)

Cancer classification using deep learning from medical image data
von: Monir, Raiyan Janik, et al.
Veröffentlicht: (2022)

Classification of retinal diseases from OCT images using deep learning models
von: Mokarrom, Md Saif, et al.
Veröffentlicht: (2024)

Brain tumor detection with convolutional neural network
von: Galib, Abrar Tahmid, et al.
Veröffentlicht: (2024)

Image processing and deep learning approach to evaluate earthquake resistance of urban buildings
von: Ahmed, Yasin, et al.
Veröffentlicht: (2018)

An efficient approach for binary classification in brain tumor detection using convolutional neural network
von: Islam, MD. Arman, et al.
Veröffentlicht: (2023)

A modern technique to detect potholes by Computer Vision and Deep Learning
von: Saif, Muntasir Mahmud, et al.
Veröffentlicht: (2023)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
von: Sharma, Tanmoyee, et al.
Veröffentlicht: (2021)

Early prediction of Alzheimer's disease using convolutional neural network
von: Abed, Mahjabeen Tamanna, et al.
Veröffentlicht: (2020)

Bangali Handwritten characters classification using Deep Convolutional Neural Network
von: Sikder, Shihab Uddin, et al.
Veröffentlicht: (2022)

An efficient deep learning approach to classify white blood cells
von: Turja, Afif Ibna Kadir Khan, et al.
Veröffentlicht: (2024)

Detection and 3D visualization of Brain tumor using deep learning and polynomial interpolation
von: Tuhin, Md. Akram Hossan, et al.
Veröffentlicht: (2019)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
von: Islam, Roman, et al.
Veröffentlicht: (2024)

Deep learning based early Glaucoma detection
von: Islam, Aabrar, et al.
Veröffentlicht: (2024)

Efficient image processing and machine learning approach for predicting retinal diseases
von: Hasib, Mehadi Hasan, et al.
Veröffentlicht: (2021)

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
von: Datta, Nirjhor, et al.
Veröffentlicht: (2024)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
von: Ifty, Md. Hasin Sarwar, et al.
Veröffentlicht: (2024)

Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
von: Fiona, Driciru, et al.
Veröffentlicht: (2024)

RetinalNet-500: a newly developed CNN model for eye disease detection
von: Toki, Sadikul Alim, et al.
Veröffentlicht: (2023)

Deep learning-based real-time pothole detection for avoiding road accident
von: Basher, Rafsan, et al.
Veröffentlicht: (2022)

Homomorphic encryption on deep learning in accurate prediction of brain tumour
von: Sarwar, Arafat, et al.
Veröffentlicht: (2023)